System and method for magnetic resonance imaging

ABSTRACT

A system and method for magnetic resonance imaging is provided. The method includes acquiring a first set of MR signals and a second set of MR signals by applying a pulse sequence on a subject. The method also includes obtaining a first data line by filling the first set of MR signals into k-space along a first trajectory, and obtaining a second data line by filling the second set of MR signals into k-space along a second trajectory. The method also includes determining a candidate k-space shift based on the first data line and the second data line, and determining a candidate gradient delay based on the candidate k-space shift obtained in each of a plurality of iterations. The method also includes reconstructing an image of the subject based on the candidate gradient delay obtained in the last iteration.

TECHNICAL FIELD

The present disclosure generally relates to magnetic resonance imaging(MRI), and more particularly, to a system and method for data processingin MRI.

BACKGROUND

Magnetic resonance imaging (MRI) is a noninvasive medical technique,which is widely used to generate images of a region of interest (ROI) byexploiting a powerful magnetic field and radio frequency (RF)techniques. During an MRI process, a set of acquired signals may beprocessed and filled into a k-space, and then data in the k-space may besubjected to Fourier transformation to reconstruct MRI images. MRIimages may suffer from ghost artifacts. To obtain images with low ghostlevels, it is important to control signal stability and timing.Unfortunately, MRI system may suffer from gradient delay, eddy currents,or imperfections in gradient amplifier. These factors may cause k-spacetrajectory deviation from design and, thus, increase ghost levels of theMRI images. Therefore, it is desirable to reduce ghost levels of the MRIimages effectively and to make the image clearer.

SUMMARY

In a first aspect of the present disclosure, a method for magneticresonance imaging is provided. The method may include one or more of thefollowing operations. A first set of MR signals and a second set of MRsignals may be acquired by applying a pulse sequence on a subject, thepulse sequence including at least an imaging pulse and a pre-scan pulse.A first data line may be obtained by filling the first set of MR signalsinto k-space along a first trajectory. A second data line may beobtained by filling the second set of MR signals into k-space along asecond trajectory. A candidate k-space shift may be determined based onthe first data line and the second data line. A plurality of iterationsmay be performed. During each of the iterations, a candidate gradientdelay may be determined based on the candidate k-space shift obtainedfrom a prior iteration; the first data line and the second data line maybe updated based on the candidate gradient delay; and the candidatek-space shift may be updated based on the updated first data line andthe updated second data line. The candidate gradient delay obtained inthe last iteration may be determined as the gradient delay. An image ofthe subject may be reconstructed based on the gradient delay.

In a second aspect of the present disclosure, a system for magneticresonance imaging is provided is provided. The system may include an MRIscanner and a processing module. The MRI scanner may be configured toacquire a first set of MR signals and a second set of MR signals byapplying a pulse sequence on a subject, the pulse sequence including atleast an imaging pulse and a pre-scan pulse. The processing module maybe configured to perform one or more of the following operations. Afirst data line may be obtained by filling the first set of MR signalsinto k-space along a first trajectory. A second data line may beobtained by filling the second set of MR signals into k-space along asecond trajectory. A candidate k-space shift may be determined based onthe first data line and the second data line. A plurality of iterationsmay be performed. During each of the iterations, a candidate gradientdelay may be determined based on the candidate k-space shift obtainedfrom a prior iteration; the first data line and the second data line maybe updated based on the candidate gradient delay; and the candidatek-space shift may be updated based on the updated first data line andthe updated second data line. The candidate gradient delay obtained inthe last iteration may be determined as the gradient delay. An image ofthe subject may be reconstructed based on the gradient delay.

In a third aspect of the present disclosure, a non-transitory computerreadable medium is provided. The non-transitory computer readable mediumstoring instructions, the instructions, when executed by a computer, maycause the computer to implement a method. The method may include one ormore of the following operations. A first set of MR signals and a secondset of MR signals may be acquired by applying a pulse sequence on asubject, the pulse sequence including at least an imaging pulse and apre-scan pulse. A first data line may be obtained by filling the firstset of MR signals into k-space along a first trajectory. A second dataline may be obtained by filling the second set of MR signals intok-space along a second trajectory. A candidate k-space shift may bedetermined based on the first data line and the second data line. Aplurality of iterations may be performed. During each of the iterations,a candidate gradient delay may be determined based on the candidatek-space shift obtained from a prior iteration; the first data line andthe second data line may be updated based on the candidate gradientdelay; and the candidate k-space shift may be updated based on theupdated first data line and the updated second data line. The candidategradient delay obtained in the last iteration may be determined as thegradient delay. An image of the subject may be reconstructed based onthe gradient delay.

In a fourth aspect of the present disclosure, a method for determining agradient delay in a magnetic resonance system is provided. The methodmay include one or more of the following operations. A first set of MRsignals and a second set of MR signals may be acquired by applying apulse sequence on a subject, the pulse sequence including at least animaging pulse and a pre-scan pulse. A first data line may be obtained byfilling the first set of MR signals into k-space along a firsttrajectory. A second data line may be obtained by filling the second setof MR signals into k-space along a second trajectory. The gradient delaymay be iteratively determined based on a k-space shift in response tothe first data line and the second data line determined based on theiterative process including iteratively updating the first data line andthe second data line after each iteration of the iterative process basedon an updated gradient delay determined by the most recent iteration ofthe iterative process.

Additional features will be set forth in part in the description whichfollows, and in part will become apparent to those skilled in the artupon examination of the following and the accompanying drawings or maybe learned by production or operation of the examples. The features ofthe present disclosure may be realized and attained by practice or useof various aspects of the methodologies, instrumentalities andcombinations set forth in the detailed examples discussed below.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is further described in terms of exemplaryembodiments. These exemplary embodiments are described in detail withreference to the drawings. These embodiments are non-limiting exemplaryembodiments, in which like reference numerals represent similarstructures throughout the several views of the drawings, and wherein:

FIG. 1A is a block diagram of a magnetic resonance imaging (MRI) systemaccording to some embodiments of the present disclosure;

FIG. 1B illustrates an exemplary architecture of an image generatoraccording to some embodiments of the present disclosure.

FIG. 2 is a flowchart of an MR scan according to some embodiments of thepresent disclosure;

FIG. 3 is a block diagram illustrating the control module 120 accordingto some embodiments of the present disclosure;

FIG. 4 is a block diagram illustrating the processing module 130according to some embodiments of the present disclosure;

FIG. 5 is a flowchart illustrating the processing of an MR signalaccording to some embodiments of the present disclosure;

FIG. 6A illustrates an exemplary timing diagram of magnetic gradientsfor an MR scan according to some embodiments of the present disclosure;

FIG. 6B illustrates another exemplary timing diagram of magneticgradients for an MR scan according to some embodiments of the presentdisclosure;

FIG. 6C shows an exemplary two-dimensional radial sampling of k-spaceaccording to some embodiments of the present disclosure;

FIG. 7 is a flowchart illustrating a process for generating a calibratedMR image according to some embodiments of the present disclosure;

FIG. 8 is a flowchart of a process for determining a gradient delayvalue according to some embodiments of the present disclosure;

FIG. 9 is a flowchart of a process for generating an image based on thegradient delay value according to some embodiments of the presentdisclosure;

FIG. 10A through FIG. 10C illustrate three MR images reconstructed, byemploying a uniform gradient waveform, without gradient delay correctionaccording to some embodiments of the present disclosure;

FIG. 10D through FIG. 10F illustrate three MR images reconstructed, byemploying a uniform gradient waveform, with gradient delay beingcorrected according to some embodiments of the present disclosure;

FIG. 10G through FIG. 10I illustrate three MR images reconstructed, byemploying a non-uniform gradient waveform, without gradient delaycorrection according to some embodiments of the present disclosure;

FIG. 10J through FIG. 10L illustrate three MR images reconstructed byemploying a nonrectangular gradient waveform, with the gradient delaybeing corrected, according to some embodiments of the presentdisclosure;

FIG. 11A through FIG. 11C illustrate three MR images reconstructed, byemploying a uniform gradient waveform, without gradient delay correctionaccording to some embodiments of the present disclosure;

FIG. 11D through FIG. 11F illustrate three MR images reconstructed, byemploying a uniform gradient waveform, with the gradient delay beingcorrected according to some embodiments of the present disclosure;

FIG. 11G through FIG. 11I illustrate three MR images reconstructed, byemploying a non-uniform gradient waveform, without gradient delaycorrection, according to some embodiments of the present disclosure; and

FIG. 11J through FIG. 11L illustrate three MR images reconstructed byemploying a non-uniform gradient waveform, with the gradient delay beingcorrected, according to some embodiments of the present disclosure.

DETAILED DESCRIPTION

In the following detailed description, numerous specific details are setforth by way of examples in order to provide a thorough understanding ofthe relevant disclosure. However, it should be apparent to those skilledin the art that the present disclosure may be practiced without suchdetails. In other instances, well known methods, procedures, systems,components, and/or circuitry have been described at a relativelyhigh-level, without detail, in order to avoid unnecessarily obscuringaspects of the present disclosure. Various modifications to thedisclosed embodiments will be readily apparent to those skilled in theart, and the general principles defined herein may be applied to otherembodiments and applications without departing from the spirits andscope of the present disclosure. Thus, the present disclosure is notlimited to the embodiments shown, but to be accorded the widest scopeconsistent with the claims.

It will be understood that the term “system,” “unit,” “module,” and/or“block” used herein are one method to distinguish different components,elements, parts, section or assembly of different level in ascendingorder. However, the terms may be displaced by other expression if theymay achieve the same purpose.

It will be understood that when a unit, module or block is referred toas being “on,” “connected to” or “coupled to” another unit, module, orblock, it may be directly on, connected or coupled to the other unit,module, or block, or intervening unit, module, or block may be present,unless the context clearly indicates otherwise. As used herein, the term“and/or” includes any and all combinations of one or more of theassociated listed items.

The terminology used herein is for the purposes of describing particularexamples and embodiments only, and is not intended to be limiting. Asused herein, the singular forms “a,” “an,” and “the” may be intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “include,”and/or “comprise,” when used in this disclosure, specify the presence ofintegers, devices, behaviors, stated features, steps, elements,operations, and/or components, but do not exclude the presence oraddition of one or more other integers, devices, behaviors, features,steps, elements, operations, components, and/or groups thereof.

FIG. 1A is a block diagram of a magnetic resonance imaging (MRI) systemaccording to some embodiments of the present disclosure. As illustrated,the MRI system 100 may include an MRI Scanner 110, a control module 120,a processing module 130, and a display module 140. The MRI Scanner 110may include a magnet module 111 and a radio frequency (RF) module 112.In some embodiments, the MRI Scanner 110 may perform a scan on asubject. In some embodiments, the scan may be an imaging scan forgenerating a magnetic resonance (MR) image, or a pre-scan forcalibrating the MRI system 100. The magnet module 111 may include a mainmagnet field generator and/or a gradient magnet field generator (notshown in FIG. 1). The main magnet field generator may create a staticmagnetic field B₀ during a scan. The main magnet field generator may beof various types including, for example, a permanent magnet, asuperconducting electromagnet, a resistive electromagnet, etc. Thegradient magnet field generator may generate magnet field gradients Gx,Gy, Gz in the “X”, “Y”, “Z” directions, respectively. As used herein,the X, Y and Z direction may represent X, Y and Z axis in a coordinatesystem. Merely by way of example, the X axis and the Z axis may be in ahorizontal plane, the X axis and the Y axis may be in a vertical plane,the Z axis may be along the rotational axis of the gantry. In someembodiments, the X axis, the Y axis, and the Z axis may be specified bythe gradient magnet field generator (i.e., gradient coils in thegradient magnet field generator). The gradient magnet field may encodeand/or readout the spatial information of the subject located within theMRI Scanner 110. In some embodiments, the magnet module 111 may generatemagnet field gradients in a set of directions during a scan. In someembodiments, the scan may be a quick calibration pre-scan to calibrate agradient delay resulted from a time delay when switching on/off thegradient magnet field generator. The magnet field gradients in thepre-scan may include an additional dephaser gradient to calibrate thegradient delay. The details of the dephaser gradient may be disclosed inother parts of the present application, for example in FIG. 6A and/orFIG. 6B, and the description thereof. Merely by way of example, themagnet module 111 may generate a first magnet field gradient in a firstdirection, a second magnet field gradient in a second direction, and athird magnet field gradient in a third direction. In some embodiments,the first, second, and third direction, may be along the X axis, the Yaxis, and the Z axis, respectively. In some embodiments, the magnetfield gradients along the X axis, the Y axis, and/or the Z axis maycorrespond to different encoding/readout directions in the k-space(e.g., the direction of the k_(x) axis, the direction of the k_(y) axis,the direction of the k_(z) axis, or any other direction). The RF module112 may include RF transmitting coils and/or receiving coils. These RFcoils may transmit RF signals to, or receive RF signals from a subjectof interest. In some embodiments, the function, size, type, geometry,position, amount, and/or magnitude of the magnet module 111 and/or ofthe RF module 112 may be determined or changed according to one or morespecific conditions. For example, according to the difference infunction and/or size, the RF coils may be classified as volume coils andlocal coils. In some embodiments, the volume coils may include birdcagecoils, transverse electromagnetic coils, surface coils, saddle coils,etc. In some embodiments of the present disclosure, the local coils mayinclude birdcage coils, solenoid coils, saddle coils, flexible coils,etc. In some embodiments, the magnet module 111 and the radio frequency(RF) module 112 may be designed to surround a subject to form a tunneltype MRI Scanner 150 (i.e. a close-bore MRI Scanner), or an open MRIScanner 110 (i.e. an open-bore MRI Scanner).

The control module 120 may control the magnet module 111 and/or the RFmodule 112 of the MRI Scanner 110, the processing module 130, and/or thedisplay module 140. Merely by way of example, the control module 120 maycontrol the magnet field gradients in the X direction, the Y direction,and the Z direction. In some embodiments, the control module 120 mayreceive information from, or send information to the MRI Scanner 110,the processing 130, and/or the display module 140. According to someembodiments, the control module 120 may receive commands from thedisplay module 140 provided by, e.g., a user, and adjust the magnetmodule 111 and/or RF module 112 to take images of a subject of interestaccording to the received commands. Merely by way of example, thecommand may relate to the polarity, waveform, strength and/or timing ofthe magnet field gradient (e.g., the dephaser gradient).

The processing module 130 may process different kinds of informationreceived from different modules. For further understanding the presentdisclosure, several examples are given below, but the examples do notlimit the scope of the present disclosure. For example, in someembodiments, the processing module 130 may process MR signals receivedfrom the RF module 112 and generate one or more MR images based on thesesignals and deliver the images to the display module 140. In someembodiments, the processing module 130 may process data input by a useror an operator via the display module 140 and transform the data intospecific commands, and supply the commands to the control module 120.

The display module 140 may receive input and/or display outputinformation. The input and/or output information may include programs,software, algorithms, data, text, number, images, voice, or the like, orany combination thereof. For example, a user or an operator may inputsome initial MR parameters or conditions to initiate a scan. As anotherexample, some information may be imported from an external resource,such as a floppy disk, a hard disk, a wireless terminal, or the like, orany combination thereof. In some embodiments, the control module 120,the processing module 130, and/or the display module 140 may beintegrated into an image generator 160. A user may set parameters in anMR scan, control the imaging procedure, view the images produced throughthe image generator 160.

It should be noted that the above description of the MRI system 100 ismerely provided for the purposes of illustration, and not intended tolimit the scope of the present disclosure. For persons having ordinaryskills in the art, multiple variations and modifications may be madeunder the teachings of the present disclosure. For example, the assemblyand/or function of the MRI system 100 may be varied or changed accordingto specific implementation scenarios. Merely by way of example, someother components may be added into the MRI system 100, such as a patientpositioning module, a gradient amplifier module, and other devices ormodules. Note that the MRI system 100 may be a traditional or asingle-modality medical system, or a multi-modality system including,e.g., a positron emission tomography-magnetic resonance imaging(PET-MRI) system, a remote medical MRI system, and others, etc. However,those variations and modifications do not depart from the scope of thepresent disclosure.

FIG. 1B illustrates an exemplary architecture of an image generatoraccording to some embodiments of the present disclosure. In someembodiments, the control module 120, the processing module 130, and/orthe display module 140, or a portion thereof, or a combination thereof,may be implemented on the image generator 160 via its hardware, softwareprogram, firmware, or a combination thereof.

The image generator 160 may include an internal communication bus 161, acentral processing unit (CPU) 162, an I/O interface 166, a COM ports165, and one or more memory devices. The internal communication bus 161may transmit data between the components (162 through 167) of the imagegenerator 160. For example, the MRI data from the disk 167 may betransmitted through internal communication bus 161 to the CUP 162 togenerate an image.

The central processing unit (CPU) 162 may execute computer instructions.The computer instructions may relate to routines, programs, objects,components, data structures, procedures, modules, etc. In someembodiments, the CPU 162 may process the data or information receivedfrom the MRI scanner 110, the control module 120, or any other componentof the MRI system 100. In some embodiments, CPU 162 may include one ormore processors. The processors may include a microcontroller, amicroprocessor, a reduced instruction set computer (MSC), an applicationspecific integrated circuits (ASICs), an application-specificinstruction-set processor (ASIP), a central processing unit (CPU), agraphics processing unit (GPU), a physics processing unit (PPU), amicrocontroller unit, a digital signal processor (DSP), a fieldprogrammable gate array (FPGA), an advanced RISC machine (ARM), aprogrammable logic device (PLD), any circuit or processor capable ofexecuting one or more functions, or the like, or any combinationsthereof. For example, the processors may include a microcontroller toprocess the MRI data received from the MRI scanner 110 for imagereconstruction.

The one or more memory devices may store the data or informationreceived from the MRI scanner 110. In some embodiments, the memorydevices may include a disk 167, a random access memory 164 (RAM), aread-only memory 163 (ROM), or the like, or any combination thereof. Thedisk 167 may be implemented by, for example, a magnetic disk, an opticaldisk, a floppy disk, an optical disk, or a zip disk, etc. The RAM 164may be implemented by, for example, a dynamic RAM (DRAM), a double daterate synchronous dynamic RAM (DDR SDRAM), a static RAM (SRAM), athyristor RAM (T-RAM), and a zero-capacitor RAM (Z-RAM), etc. The ROM163 may be implemented by, for example, a mask ROM (MROM), aprogrammable ROM (PROM), an erasable programmable ROM (PEROM), anelectrically erasable programmable ROM (EEPROM), a compact disk ROM(CD-ROM), and a digital versatile disk ROM, etc. In some embodiments,the memory devices may store one or more programs and/or instructions toperform exemplary methods described in the present disclosure. Forexample, the ROM 163 may store a program or an algorithm forreconstructing an MR image based on the MR data.

The image generator 160 may include one or more COM ports 165 connectedto a network to furnish data communications. The communication ports(COM ports) 165 may transmit information to or receive information fromMRI scanner 110 via a network. In some embodiments, communication ports165 may include a wired port (e.g., a Universal Serial Bus (USB), a HighDefinition Multimedia Interface (HDMI), a wireless port (such as aBluetooth port, an infrared interface, and a WiFi port), or the like, orany combination thereof.

The I/O interface 166 may support information input or output betweenthe image generator 160 and one or more peripherals. In someembodiments, the peripherals may include a terminal, a keyboard, a touchscreen, a cursor control device, a remote controller, or the like, orany combination thereof. The terminal may include, for example, a mobiledevice (e.g., a smart phone, a smart watch, a laptop computer, or thelike), a personal computer, or the like, or any combination thereof. Forexample, the terminal may be implemented by a computer 168, which may bea general purpose computer or a specially designed computer. The cursorcontrol device may include a mouse, a trackball, or cursor directionkeys to communicate direction information and command selections to, forexample, the processing module 130 or control cursor movement on adisplay device.

The information input and/or output via I/O interface 166 may includeprograms, software, algorithms, data, text, number, images, voices, orthe like, or any combination thereof. For example, a user may input someinitial parameters or conditions to initiate an MRI data processing. Insome embodiments, the information input via I/O interface 166 may beinput via a keyboard, a touch screen, a voice sensor, a motion sensor, abrain monitoring system, or any other devices. The information outputvia I/O interface 166 may be may be transmitted to the display module140, a loud speaker, a printer, a computing device, or the like, or acombination thereof.

Those skilled in the art will recognize that the present teachings areamenable to a variety of modifications and/or enhancements. For example,although the implementation of various components described herein maybe embodied in a hardware device, it may also be implemented as asoftware only solution, e.g., an installation on an existing server. Inaddition, the image processing device as disclosed herein may beimplemented as a firmware, firmware/software combination,firmware/hardware combination, or a hardware/firmware/softwarecombination.

FIG. 2 is a flowchart of an MR scan according to some embodiments of thepresent disclosure. In 202, an MR parameter may be set. The MR parametermay relate to an MR scanning, a protocol selection, a signalacquisition, a data processing, a data storage, a data calibration, animage generation, or the like, or any combination thereof. Merely by wayof example, the MR parameter may include an image contrast and/or ratio,a region of interest (ROI), slice thickness, an imaging type (e.g., T1weighted imaging, T2 weighted imaging, proton density weighted imaging,etc.), a spin echo type (spin echo, fast spin echo (FSE), fast recoveryFSE, single shot FSE, gradient recalled echo, fast imaging withstead-state procession, and etc.), a flip angle value, acquisition time(TA), echo time (TE), repetition time (TR), echo train length (ETL), thenumber of phases, the number of excitations (NEX), inversion time,bandwidth (e.g., RF receiver bandwidth, RF transmitter bandwidth, etc.),or the like, or any combination thereof. In some embodiments, the MRparameter may be set in the control module 120. In some embodiments, theMR parameter may be set via the image generator 160 through a userinterface.

In 204, an MR scan may be performed by, for example, the MRI Scanner110. In some embodiments, the MR scan may be an imaging scan forgenerating an image, or a pre-scan for calibrating the MRI system 100.In some embodiments, an MR parameter including a pulse sequence may besent to the MRI Scanner 110 to generate RF excitation pulses andmagnetic field gradients during the MR scan. The pulse sequence may be,for example, a spin echo (SE) sequence, a fast spin echo (FSE) sequence,an ultrashort echo-time (UTE) sequence, a gradient echo (GRE) sequence,etc. Merely by way of example, a radial 3D UTE sequence may be provideto the MRI Scanner 110. In some embodiments, the pulse sequence may besent to the MRI Scanner 110 in a form of a timing diagram. In someembodiments, the MR scan may be a pre-scan, within which a few steps,for example, quick shimming, coil tuning/matching, center frequencycalibration, and transmitter gain adjustment, may be included. In someembodiments, the pre-scan may be performed to calibrate a gradient delaycaused by the time delay when switching on/off the gradient magneticfield generator. In some embodiments, an MR signal may be acquiredduring the MR scan. In some embodiments, the acquired MR signal may bean analog signal.

In 206, the MR signal acquired during the MR scan may be processed by,for example, the processing module 130. Various signal processingmethods may be applied to process the acquired signal. Merely by way ofexample, the signal processing methods may include analog-to-digitalconversion, linear fitting, 2D Fourier transform (2D FT), fast Fouriertransform (FFT), interpolation algorithm, regridding, or the like, orany combination thereof. In some embodiments, the acquired signal may beconverted to a set of discrete data. Furthermore, the discrete data maybe processed to fill into the k-space. Also, the filled k-space may beprocessed to calibrate the gradient delay in an imaging scan.

In 208, an MR image may be generated based on the processed signal. Insome embodiments, the image may be generated by repeating 202 through206 for a certain number of times. In some embodiments, the certainnumber of times may be determined by the MRI system 100 or provided by auser (e.g., a doctor). The generated image may be a T₁-weighted image, aT₂-weighted image, a PD (proton density)-weighted image, a FLAIR (fluidattenuated inversion recovery) image, or the like. In some embodiments,the image may be further processed to generate a report including thereconstructed image. The image and/or the generated report may be outputto a related device (e.g., to be printed, to be displayed, or the like).

It should be noted that the above description is provided for thepurposes of illustration, not intended to limit the scope of the presentdisclosure. For persons having ordinary skills in the art, multiplevariations and modifications may be reduced to practice in the light ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure. For example, theprocess may further include an operation between 204 and 206 for storingthe acquired MR signal.

FIG. 3 is a block diagram illustrating the control module 120 accordingto some embodiments of the present disclosure. The control module 120may include an X gradient control unit 301, a Y gradient control unit302, a Z gradient control unit 303, and an RF control unit 304.

The X gradient control unit 301, the Y gradient control unit 302, andthe Z gradient control unit 303 may control the magnet module 111 togenerate magnet field gradients in the X direction, the Y direction, andthe Z direction, respectively. The X gradient control unit 301 maycontrol the polarity, waveform, strength, and/or timing of the magnetfield gradients in the X direction. The Y gradient control unit 302 maycontrol the polarity, waveform, strength and/or timing of the magnetfield gradient in the Y direction. The Z gradient control unit 303 maycontrol the polarity, waveform, strength and/or timing of the magnetfield gradients in the Z direction. In some embodiments, the magnetfield gradients in the X direction, the Y direction, or the Z directionmay include an encoding gradient and/or a readout gradient. As usedherein, the encoding gradient may be used to spatially encoding signalsfrom a part of an imaged subject (e.g., an organ, a tissue, etc.) fromanother; the readout gradient may be used to readout echo signals thatmay be used to generate an MR image. The X gradient control unit 301,the Y gradient control unit 302, or the Z gradient control unit 303 maybe coupled with the magnet module 111, the processing module 130, and/orthe display module. Merely by way of example, the X gradient controlunit 301 may receive a command sent from the display module 140 providedby, e.g., a user. In some embodiments, the command may relate to thetiming sequence of the readout gradient in the X direction. In someembodiments, the command may be sent to the magnet module 111.

The RF control unit 304 may control the RF module 112 to generate RFexcitation pulses. In some embodiments, the RF control unit 304 maycontrol the radio frequency, the phase, the amplitude and/or thewaveform of the radio frequency pulse. In some embodiments, the RFcontrol module 120 may be coupled with the RF module 112, the processingmodule 130, and/or the display module 140. Merely by way of example, theRF control unit 304 may send a command to the RF module 112 to controlthe radio frequency of the radio frequency pulse generated thereby.

It should be noted that the above description of the control module 120is merely provided for the purposes of illustration, and not intended tolimit the scope of the present disclosure. For persons having ordinaryskills in the art, multiple variations and modifications may be madeunder the teachings of the present disclosure. For example, the assemblyand/or function of the control module 120 may be varied or changedaccording to specific implementation scenarios. Merely by way ofexample, a magnet field gradient in an arbitrary direction may begenerated by a specifically designed gradient control unit (e.g.,similar with the X/Y/Z gradient control unit but in a differentdirection), or by a superposition of the magnet field gradients in theX, Y, and/or Z direction. However, those variations and modifications donot depart from the scope of the present disclosure.

FIG. 4 is a block diagram illustrating the processing module 130according to some embodiments of the present disclosure. Note that theconstruction of the processing module 130 may have some othervariations, and that FIG. 4 is provided for illustration purposes. Theprocessing module 130 illustrated in FIG. 1 may process informationbefore, during, or after an MR scan. The processing module 130 may be acentral processing unit (CPU), an application-specific integratedcircuit (ASIC), an application-specific instruction-set processor(ASIP), a graphics processing unit (GPU), a physics processing unit(PPU), a microcontroller unit, a digital signal processor (DSP), a fieldprogrammable gate array (FPGA), an ARM, or the like, or any combinationthereof. As shown in FIG. 4, the processing module 130 may include acomputing unit 401, an image generation unit 402, a storage 403, and anA/D converter 404.

The computing unit 401 may determine different kinds of informationgenerated from the MRI Scanner 110, or received from the control module120 and/or display module 140. In some embodiments, the information fromthe MRI Scanner 110 may be a plurality of MR signals of an imagedsubject. In some embodiments, the MR signals may include an echo wave, ahalf echo wave, or a signal between an echo wave and a half echo wave(also referred to as “partial echo signal”). In some embodiments, thecomputing unit 401 may determine a gradient delay value based on the MRsignals. The gradient delay value may be a gradient delay value for thegradient magnetic field in the X direction, the Y direction, the Zdirection, or any other directions in a coordinate system. In someembodiments, the gradient delay value may correspond to a k-space shiftalong a radial spoke in a 3D k-space coordinate. In some embodiments,the radial spoke may be determined by the condition of the MRI system100. In some embodiments, the k-space shift along the radial spoke maybe determined based on the gradient delay value for the X direction, theY direction, and/or the Z direction. In some embodiments, the gradientdelay value may be used to calibrate k-space data (also referred to as“k-space data line”) generated by an imaging scan. In some embodiments,the gradient delay value may be generated by performing the pre-scan. Insome embodiments, the pre-scan may be performed for calibrating the MRIsystem 100, while the imaging scan may be performed for generating amagnetic resonance (MR) image. The k-space data may be generated byfilling an MR signal generated by an imaging scan into the k-space. Forexample, a first set of MR signals may be filled into the k-space alonga specific trajectory, forming a first data line in the k-space.

In some embodiments, the information from the control module 120 mayinclude information about the MRI Scanner 110, the magnet module 111, apatient position (e.g., within the MRI system 100), the RF module 112,or the like, or any combination thereof. In some embodiments, theinformation may be a patient position, the main and/or gradient magnetintensity, the radio frequency phase and/or amplitude, etc. Theinformation from the display module 140 may include information from auser and/or other external resource. Exemplary information from a usermay include parameters regarding image contrast and/or ratio, a subjectof interest (e.g., the type of tissue to be imaged, etc.), slicethickness, an imaging type (e.g., T1 weighted imaging, T2 weightedimaging, proton density weighted imaging, etc.), T1, T2, a spin echotype (e.g., spin echo, fast spin echo (FSE), fast recovery FSE, singleshot FSE, gradient recalled echo, fast imaging with stead-stateprocession, and so on), a flip angle value, acquisition time (TA), echotime (TE), repetition time (TR), echo train length (ETL), the number ofphases, the number of excitations (NEX), inversion time, bandwidth(e.g., RF receiver bandwidth, RF transmitter bandwidth, etc.), or thelike, or any combination thereof.

The computing unit 401 may process the different kinds of informationacquired from the MRI Scanner 110, control module 120 and/or displaymodule 140. Various operations may be performed on t different kinds ofinformation. Exemplary operations may include Fourier transform (FFT),regridding, interpolation algorithm, orthographic projection, matrixtransformation, least square algorithm, linear fitting, recursion, abisection method, an exhaustive search (or brute-force search), a greedyalgorithm, a divide and conquer algorithm, a dynamic programming method,an iterative method, a branch-and-bound algorithm, a backtrackingalgorithm, or the like, or any combination thereof. In some embodiment,the computing unit 410 may generate a set of k-space data points to fillthe k-space based on the acquired echo signal utilizing the computingmethods mentioned above. In some embodiment, the computing unit 410 maydetermine a gradient delay value representing the k-space shiftutilizing one or more of the operations mentioned above.

The image generation unit 402 may connect to the computing unit 401, theMRI Scanner 110, the Magnet module 111, the display module 140, and/orthe storage 403. In some embodiments, the image generation unit 402 mayreceive information from the MRI Scanner 110, the computing unit 401,and/or the storage 403. In some embodiments, the information may be anMR signal, or k-space data line relating to the MR signal. Merely by wayof example, the image generation unit 402 may generate an MR image basedon the calibrated k-space data line. The image generation unit 402 mayemploy different kinds of imaging reconstruction techniques for theimage reconstruction procedure. Exemplary image reconstructiontechniques may include Fourier reconstruction, constrained imagereconstruction, regularized image reconstruction in parallel MRI, or thelike, or any combination thereof.

The storage 403 may store the information that may be used by thecomputing unit 401 and/or the image generation unit 402. The informationmay include programs, software, algorithms, data, text, number, imagesand some other information. These examples are provided here forillustration purposes, and not intended to limit the scope of thepresent disclosure. Algorithms stored in the storage 403 may includerecursion, a bisection method, a divide and conquer algorithm, a dynamicprogramming method, an iterative method, a branch-and-bound algorithm, abacktracking algorithm, or the like, or any combination thereof. In someembodiments, the storage 403 may store MR signals generated by the MRIscanner 110.

The A/D converter 404 may convert analog MR signals to digital MRsignals. In some embodiments, one or more parameters may be set beforeor during the conversion, e.g., voltage, current, rate, samplingfrequency, or the like, or a combination thereof. The converted MRsignals may be stored in the storage 403.

It should be noted that the above description of the processing module130 is merely provided for the purposes of illustration, and notintended to limit the scope of the present disclosure. For personshaving ordinary skills in the art, multiple variations or modificationsmay be made under the teachings of the present disclosure. For example,the assembly and/or function of processing module 130 may be varied orchanged. In some embodiments, the computing unit 401 and the imagegeneration unit 402 may share one storage 403. While in someembodiments, the computing unit 401 and the image generation unit 402may have their own storage blocks, respectively. However, thosevariations and modifications do not depart from the scope of the presentdisclosure.

FIG. 5 is a flowchart illustrating the processing of an MR signalaccording to some embodiments of the present disclosure. In 502, an echosignal may be acquired. The echo signal may be echo wave acquired by,for example, the MRI Scanner 110. In some embodiments, the acquired echosignal may be a spin echo (SE), 3D fast spin echo (3D F SE), gradientecho (GRE), fast double echo (FADE). In some embodiments, the acquiredecho signal may be a free induction decay (FID) signal. The echo signalmay be a half echo wave, a full echo wave, or a partial echo signal. Insome embodiments, the echo signal may be an analog signal. The echosignal may be generated in an imaging scan or a pre-scan by, forexample, applying a dephaser gradient as illustrated in FIG. 6A and/orFIG. 6B, and the description thereof. In some embodiments, the signalmay be acquired by the MRI Scanner 110.

In 504, the acquired echo signal may be stored in the k-space. In someembodiments, the acquired echo signal may be processed before beingstored into the k-space. Exemplary operations may include high-passfiltering, smoothing algorithm, analog to digital conversion, etc.Specifically, the operations may be performed by converting the analogecho signal into a digital signal by the AD convertor 404. In someembodiments, the acquired echo signal may be sampled according to asampling algorithm to generate a set of discrete data to be filled intothe k-space. There may be various sampling technique for the filling ofthe k-space with the acquired signal, including Cartesian sampling (rowby row), radial sampling, spiral sampling, zig-zag sampling, etc. Asused herein, the radial sampling may refer to a sampling technique inwhich an echo signal is filled along a radial spoke (also referred to as“a trajectory”) to form a data line in the k-space. For athree-dimensional radial sampling, the k-space may have a shape of asphere, and the k-space may be filled along radial spokes of the sphere.In some embodiments, the radial spokes may start from the center of thek-space, and end on a spherical surface in the k-space (also referred toas “center out trajectories”). Merely by way of example, under theradial sampling, the acquired echo signal may be filled along radialspokes in the k-space.

In 506, the echo signal stored in the k-space may be processed. Variousoperations may be utilized to process the echo signal stored in thek-space. For example, the various operations may include linear fitting,least squares operation, 2D Fourier transform (2D FT), Z-transform,Laplace transform, principle component analysis (PCA), nearest neighborinterpolation, regridding, iteration, or the like, or any combinationthereof. In some embodiments, the echo signal stored in the k-space maybe calibrated and transformed into an image domain. In some embodiments,the echo signal may be further processed with one or more operationsexemplified above to eliminate errors or artifacts resulted from, forexample, motion, interference, shadowing, incomplete data, k-spaceshift, k-space distortion, over sampling, under sampling, etc. In someembodiments, step 502 through step 506 may be repeated for obtainingadequate k-space data lines before the image reconstruction isperformed.

In 508, an image may be reconstructed based on the processed echosignal. Exemplary image reconstruction techniques may include Fourierreconstruction, inverse Fourier transform, constrained imagereconstruction, regularized image reconstruction in parallel MRI, or thelike, or any combination thereof. In some embodiments, the reconstructedimage may be further processed to generate a report regarding thereconstructed image. In some embodiments, one or more post processingoperations may be applied to the reconstructed image. The postprocessing operations may relate to geometrical processing, arithmeticprocessing, image enhancement, image restoration, 3D imagereconstruction, or the like, or any combination thereof. Merely by wayof example, the post processing operations may include magnification,distortion correction, image sharpening, image softening, pseudo colorprocessing, and/or wiener filtering. In some embodiments, the image maybe compressed to a standard format for handling, printing, storing, ortransmitting the MRI data, for example, digital imaging andcommunications in medicine (DICOM).

It should be noted that the above description is provided for thepurposes of illustration, not intended to limit the scope of the presentdisclosure. For persons having ordinary skills in the art, multiplevariations and modifications may be reduced to practice in the light ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure. For example, forreconstruction of non-Cartesian MRI data (e.g., data obtained fromradial sampling), the process may return to 504 after signal processing,in which regridding may be applied and the echo signal may be stored ina Cartesian k-space.

FIG. 6A and FIG. 6B show two exemplary timing diagram of pulse sequencesfor an MR scan according to some embodiments of the present disclosure.In some embodiments, the MR scan may include a pre-san pulse configuredto calibrate the MRI system 100. The timing diagram may indicate aseries of radio-frequency (RF) excitation pulses and magnetic fieldgradient pulses (also referred to as “readout gradients”) applied in theMR scan. An echo signal may be generated by applying the RF excitationpluses and the readout gradients in an MR scan. In some embodiments, apartial echo signal may be acquired. In some embodiments, a full echosignal may be acquired. The acquisition of the echo signal may beimplemented by an analog-to-digital convertor (ADC), when the acquiredecho signal is filled into k-space. As is illustrated in FIG. 6A and/orFIG. 6B, the readout gradients may include a dephasing gradient 602(also referred to as “imaging pulse”), a rephrasing gradient 603, and aspoiler 604. In some embodiments, a pre-scan may be performed by addinga dephaser gradient 601-1 (also referred to as “pre-scan pulse”) and/ora dephaser gradient 601-2 in the readout gradients. As is illustrated inFIG. 6A, the dephaser gradient 601-1 may be applied between theradio-frequency (RF) excitation pulse and the ramp up of the dephasinggradient 602. The polarity of the dephaser gradient 601-1 may beopposite to the polarity of the dephasing gradient 602. As isillustrated in FIG. 6B, the dephaser gradient 601-2 may be appliedbetween the dephasing gradient 602 and the ramp up of the rephrasinggradient 603. The polarity of the dephaser gradient 601-2 may be samewith the polarity of the dephasing gradient 602. In some embodiments,the waveform of the dephaser gradient 601-1 and/or the dephaser gradient601-2, the dephasing gradient 602, the rephrasing gradient 603, and/orthe spoiler 604 may be uniform (e.g., rectangle, trapezoid, etc.) ornon-uniform (e.g., asymmetric waveform). In some embodiments, thereadout gradient may be applied in the X direction, in the Y direction,in the Z direction, or in any other direction through the gradient coilsin different directions of the MRI system 100.

FIG. 6C shows an exemplary two-dimensional radial sampling of k-spaceaccording to some embodiments of the present disclosure. For atwo-dimensional radial sampling, the k-space that constituted by Xdirection in the k-space (i.e., k_(x)) and Y direction in the k-space(i.e., k_(y)) may have a round shape, and radial spokes in the k-spacemay start from the center of the k-space, and end on a round surface(also referred to as “center out trajectories”). The echo signalgenerated by applying a pulse sequence (for example, the pulse sequencesas illustrated in FIG. 6A and/or FIG. 6B) may be filled into k-space toform a data line along a certain trajectory. In some embodiments, radialsampling may be applied on a partial echo signal acquired in thepre-scan. The acquired partial echo signal may be filled into k-spacealong a corresponding radial spoke (trajectory) to form a data line inthe k-space. In some embodiments, the partial echo signal may be filledinto the radial spoke passing through the k-space center, and ending onthe round surface. Similarly, for a three-dimensional radial sampling,the k-space that constituted by X direction in the k-space (i.e.,k_(x)), Y direction in the k-space (i.e., k_(y)) and Z direction in thek-space (i.e., k_(z)) may have a shape of sphere. The spatial samplingof the three-dimensional k-space may be similar to the two-dimensionalradial sampling as described elsewhere in the disclosure.

FIG. 7 is a flowchart illustrating a process for generating a calibratedMR image according to some embodiments of the present disclosure. In702, a pre-scan may be performed. The pre-scan may be performed on aphantom or on a subject (e.g., a patient). As used herein, a phantom mayrefer to a specially designed subject that is scanned or imaged toevaluate the performance of the imaging devices. In some embodiments,the pre-scan may be performed for anatomical regions, for example, thebrain of a subject, a lung of a subject, the heart of a subject, or thelike, or a combination thereof. In some embodiments, the pre-scan may beperformed for the same region as in an imaging scan.

The pre-scan may be performed by applying the dephaser gradient 601-1 inthe readout gradient as illustrated in FIG. 6A and the descriptionthereof. The dephaser gradient 601-1 may occur between theradio-frequency (RF) excitation pulse and the ramp up of the dephasinggradient 602. In some embodiments, a partial echo signal may be acquiredduring the pre-scan. In some embodiments, a plurality of partial echoesmay be acquired by repetitions of the RF excitation pulses and thereadout gradients including the dephaser gradient 601-1.

The acquired partial echo signals may be filled into the k-space. Thek-space may be a two dimensional (2D) k-space or a three dimensional(3D) k-space. In some embodiments, multiple points may be selected fromthe partial echo signal to be filled, as k-space data points, into thek-space in the k-space sampling. Exemplary k-space sampling techniquesmay include Cartesian sampling, spiral sampling, radial sampling,zig-zag sampling, etc. In some embodiments, radial sampling may beapplied in the pre-scan, the partial echo signal may be filled, as thek-space data points, into k-space along the radial spokes. The points inthe partial echo signal corresponding to the k-space data line along aradial spoke may be generated by activating magnetic field gradients ina certain direction. The activation of the magnetic field gradients maybe achieved by the X gradient control unit 301, Y gradient control unit302, and/or Z gradient control unit 303.

In the pre-scan, k-space data lines along certain radial spokes may beacquired. In some embodiments, a first k-space data line along a firsttrajectory may be acquired, and a second k-space data line along asecond trajectory, with a reverse direction relative to the firsttrajectory, may be acquired. For example, the first k-space data linemay correspond to a first trajectory in the k-space with an angle of 0°,and the second k-space data line may correspond to a second trajectoryin the k-space with an angle of 180°.

In 704, a spatial distribution of phase difference in the image domaincorresponding to different radial spokes in the k-space may bedetermined. Firstly, the k-space data line along a radial spoke may betransformed into an image domain to generate a corresponding imagesignal. The transformation may be performed according to an algorithmincluding, for example, Fourier transform (FT), fast Fourier transform(FFT), non-uniform fast Fourier transform (NUFFT), or the like, or anycombination thereof. In some embodiments, one or more other operationsincluding regridding, interpolation, etc., may be performed in thetransformation. By way of the transformation, a first image signalcorresponding to the first k-space data line and a second image signalcorresponding to the second k-space data line may be obtained. In someembodiments, the first image signal and/or the second image signal maybe one-dimensional signal(s) whose amplitude may vary along a directionin the image domain corresponding to the first and second radial spokesin the k-space. As used herein, an image signal may include amplitude,frequency, and phase information of the k-space data points along theradial spoke. In some embodiments, the image signal may take a form of aphase curve along the radial spoke. The horizontal axis of the phasecurve may represent k-space data points along a radial spoke, and thevertical axis may represent the phase value of the k-space data points.

In some embodiments, a first phase curve and a second phase curve in theimage space may be determined. The first phase curve may correspond tothe first k-space data line along the first radial spoke. The secondphase curve may correspond to the second k-space data line along theopposite radial spoke. The phase difference between the first phasecurve and the second phase curve may be determined. In some embodiments,the phase difference may be represented by a phase difference curve. Insome embodiments, the slope of the phase difference curve may bedetermined. In some embodiments, the slope of the phase difference curvemay represent the spatial distribution of phase difference for onedimensional image signal in image space. The slope may be a constant insome cases (i.e., the phase difference curve may be a straight line incertain regions).

In 706, a gradient delay value may be determined based on the spatialdistribution of the phase difference. The gradient delay value mayrepresent a delay in the time of the gradient magnetic field generatedin the MR scan. In some embodiments, the gradient delay may lead to ashift of the k-space data line along a radial spoke in a certaindirection. For example, the gradient delay may lead to a shift (theshift may be different for different data points on the line) of thek-space relative to the center of the k-space (also referred to as“k-space center”). A k-space shift value may be generated to calibratethe k-space shift by detecting the k-space center. In some embodiments,the k-space shift value may be determined based on the phase differencebetween the first phase curve and the second phase curve. In someembodiments, the k-space shift value may be determined based on thespatial distribution of the phase difference (e.g., the slope of thephase difference curve). In some embodiments, the k-space shift valuemay be determined based on the relationship between the image space andthe k-space. The k-space shift value may be assessed based on the shiftproperty of the Fourier transform. More description regarding thek-space shift value may be found in elsewhere in the present disclosure.See, for example, FIG. 8 and the description thereof. Based on thek-space shift value, the gradient delay value may be determined. In someembodiments, a coefficient may be provided as one of the factors for thedetermination of the gradient delay value. The coefficient may be set byan operator, determined based on the status of the MRI system 100, timeefficiency, or the like, or a combination thereof.

In 708, k-space shift values for a radial spoke in the k-space may bedetermined based on the gradient delay value obtained in 706. In someembodiments, the gradient delay values in different directions in thecoordinate system may be determined by carrying out 702 through 706while performing pre-scans. The gradient delay values in differentdirections may be further transformed to the magnetic field gradientdelay values for the X axis, the Y axis, and the Z axis of thecoordinate system. In some embodiments, the gradient delay values indifferent directions may be converted into gradient delay values on theX axis, the Y axis, and the Z axis of the coordinate system by anorthographic projection operation. The X axis, the Y axis, and the Zaxis may correspond to the positions of the X gradient coils, the Ygradient coils, and the Z gradient coils, a patient body, or theorientation of the bed, etc. Then, the k-space shift values for anarbitrary radial spoke in the k-space may be determined based on themagnetic field gradient delay values on the X axis, the Y axis, and theZ axis.

In 710, an imaging scan may be performed to generate an image based onthe k-space shift values. In some embodiments, the k-space data linegenerated by the imaging scan may be calibrated based on the k-spaceshift values obtained in 708. The imaging scan may be an MRI scan forgenerating images. In some embodiments, the imaging scan may be a 3Dradial UTE scan. The k-space data line along a radial spoke generated bythe imaging scan may be calibrated based on the k-space shift values forthe radial spoke.

An image may be reconstructed based on the calibrated k-space data linegenerated by the imaging scan. The reconstruction technique may includeFourier transform (FT), fast Fourier transform (FFT), non-uniform fastFourier transform (NUFFT). The k-space data points along the calibratedk-space data line may be non-uniform due to ramp sampling. As usedherein, the non-uniform k-space data points may refer to the data pointsobtained by k-space sampling technique other than Cartesian sampling,such as radial sampling. In some embodiments, the non-uniform k-spacedata points may be converted to uniform k-space data points before animage is generated by performing regridding or interpolation. In someembodiments, an image may be generated based on the non-uniform k-spacedata points by non-uniform fast Fourier transform (NUFFT). In someembodiments, apodization may be performed to correct for the effect ofregridding kernel. The reconstructed image may be a T₁-weighted image, aT₂-weighted image, a PD-weighted image, a FLAIR image, etc.

It should be noted that the above description is provided for thepurposes of illustration, not intended to limit the scope of the presentdisclosure. For persons having ordinary skills in the art, multiplevariations and modifications may be reduced to practice in the light ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure. For example,magnetic field gradient delay values for three arbitrary directions inthe coordinate system may be used to determine the gradient delay valueon the X axis, the Y axis, and the Z axis. In some embodiments, one ofthe three arbitrary directions may point out of the plane constituted bythe other two directions.

FIG. 8 is a flowchart of a process for determining the gradient delayvalue according to some embodiments of the present disclosure. In 802, apre-scan may be performed. A parameter for the pre-scan may be set inthe control module 120. In some embodiments, the parameter may includethe gradient field, the sampling technique, the scanning direction, thepulse sequence, the echo time, etc. The pre-scan may include thedephaser gradient 601-1 in the readout gradient that may occur betweenthe RF excitation pulse and the ramp up of the dephasing gradient, e.g.,602 as illustrated in FIG. 6A. In some embodiments, the dephasergradient with a uniform gradient waveform (for example, triangle,trapezoid, rectangle) may be set for the pre-scan. In some embodiments,the dephaser gradient with a non-uniform gradient waveform (for example,with imperfections on an otherwise uniform gradient waveform), such as aslight fluctuation caused by the instability of the magnetic field, maybe set for the pre-scan. In some embodiments, the imperfections of thegradient field may be calibrated based on the pre-scan. In someembodiments, one or more calibration technique may be utilized for theactual shape of the gradient field. See, for example, the k-spacetrajectory measurement technique as described in Jeff H. Duyn, SimpleCorrection Method for k-Space Trajectory Deviations in MRI, JMR,150-153(1998), which is hereby incorporated by reference.

The pre-scan may be performed prior to an imaging scan with a timeinterval between the pre-scan and the imaging scan. In some embodiments,the pre-scan may be performed prior to the imaging scan to determine agradient delay value to calibrate the k-space shift. In someembodiments, the pre-scan may be performed before the imaging scanwithout a time interval.

In 804, an echo signal generated by the pre-scan may be acquired. Insome embodiments, the generated signal may be the partial echo signalillustrated in FIG. 6A and/or FIG. 6B, and the description thereof.During the pre-scan, the echo signal may be generated by an RFexcitation pulse and a gradient reversal. The gradient reversal may beimplemented by the dephaser gradient in conjunction with the firstgradient field in the readout gradient (e.g., dephasing gradient 602 inFIG. 6A and/or FIG. 6B). In some embodiments, the echo signal may begenerated at the ramp up or the plateau of the readout gradient. In someembodiments, a plurality of echo signals may be generated by repetitionsof the gradient reversal in the pre-scan.

In 806, a k-space data line may be generated based on the echo signalacquired in 804. The acquired echo signal may be filled into thek-space. In some embodiments, multiple points may be selected from theacquired echo signal to fill the k-space as k-space data points. Themultiple points may be selected at a regular intervals or varyingintervals. In some embodiments, the intervals may be determined by thegradient field as set in the pre-scan. In some embodiments, the multiplepoints may be filled into the k-space according to a k-space samplingtechnique. Exemplary k-space sampling techniques may include Cartesiansampling, spiral sampling, radial sampling, zig-zag sampling, etc.

For a three-dimensional radial sampling, the echo signal may be filledalong a trajectory in the k-space that passes through the k-spacecenter, and ends on a spherical surface in the k-space (also referred toas “boarder region”). In some embodiments, radial sampling may beapplied in the pre-scan, and the acquired echo signal may be filled intok-space along a corresponding radial spoke.

The k-space data lines along radial spokes in different directions(including k_(x), k_(y) and k_(z)) may be acquired. In some embodiments,the k-space data lines along radial spokes in the positive direction andthe negative direction along the X axis, the Y axis, or the Z axis inthe k-space may be acquired. In some embodiments, a first k-space dataline along a first trajectory in the k-space may be acquired, and asecond k-space data line along a second trajectory in the oppositedirection may be acquired subsequently. For example, the firsttrajectory and the second trajectory may be center-out trajectories, andthe first trajectory may be opposite to the second trajectory. In someembodiments, the first k-space data line and the second k-space dataline may be used to determine the gradient delay in a certain directionin a coordinate system in the image domain. For example, a first k-spacedata line along the positive direction of the X axis in the k-space anda second k-space data line along the negative direction of the X axismay be acquired to determine a gradient delay value.

In some embodiments, the k-space data line may be updated according tocandidate gradient delay values. See description in connection with 814.The candidate gradient delay values may be generated by way of aplurality of iterations. In some embodiments, the iteration may stopwhen an eligible gradient delay value is obtained based on the candidategradient delay values.

In 808, an image signal may be generated based on the k-space data line.The k-space data line may be converted into the image signal based on analgorithm. Exemplary algorithm may include Fourier transform (FT), fastFourier transform (FT), discrete Fourier transform (DFT), or the like,or any combination thereof. In some embodiments, non-uniform k-spacedata points along the k-space data line may be subject to anintermediate processing to generate corresponding uniform k-space datapoints that are further converted into an image signal. Merely by way ofexample, the intermediate processing may include regridding,interpolation, etc. For example, non-uniform k-space data points may beconverted into uniform k-space data points by piecewise constantinterpolation, linear interpolation, polynomial interpolation, splineinterpolation, multivariate interpolation, etc. As another example,non-uniform k-space data points may be converted into uniform k-spacedata points by Jacobian regridding, Voronoi regridding, Jacksonregridding, Pipe regridding, etc. Then, the uniform k-space data pointsmay be transformed into an image signal. In some embodiments, thetransformation may be accomplished by FT, FFT, DFT, etc. In someembodiments, the non-uniform k-space data points may be transformed intoan image signal directly by non-uniform Fourier transform (NUFFT).

In 810, a spatial distribution of phase difference in the image domainthat corresponds to the radial spokes in the k-space may be generated.For illustration purposes, the radial spokes may be positioned along thek_(x) in the following operations, which should not limit the scope ofthe present disclosure. A first k-space data line S₊(k) along thepositive direction of the X axis, and a second k-space data line S⁻(k)along the negative direction of the X axis may be acquired. Inconsideration of the k-space shift along the X axis due to gradientdelay, the first k-space data line S₊(k) may be expressed as S(k−k₀),and the second k-space data line S⁻(k) may be expressed as S(k+k₀). Thecorresponding image signal I₊(x) in the image domain for the firstsignal S₊(k) and I⁻(x) for the second signal S⁻(k) may be determinedaccording to the following Equations (1) and (2), respectively:

I ₊(x)=FT(S ₊(x))=I(x)exp^((i·k) ⁰ ^(·x)).   (1)

I ⁻(x)=FT(S ⁻(x))=I(x)exp^((−i·k) ⁰ ^(·x)).   (2)

where FT may denote Fourier transform, and k₀ may denote the k-spaceshift due to the gradient delay. In some embodiments, the phasedifference Δφ in the image domain between the first image signal andsecond image signal may be determined. Through Equations (1) and (2),the spatial distribution of the phase difference δ_(x) between the firstsignal I₊(x) and the second signal I⁻(x) (the phase difference along theX axis, e.g., the slope of the phase difference curve) may be determinedaccording to the following Equation (3):

$\begin{matrix}{\delta_{x} = {\frac{\Delta\phi}{x}.}} & (3)\end{matrix}$

The phase difference Δφ between signal I₊(x) and I⁻(x) in the imagedomain may be determined based on Equation (4) in accordance withEquations (1) and (2):

Δφ=2k ₀ ·x.   (4)

Via Equations (3) and (4), the spatial distribution of the phasedifference in the image domain (e.g., the slope of the phase differencecurve) may be determined based on equation (5).

δ_(x)=2k₀.   (5)

Therefore, the phase difference curve is linear along the X axis; inanother word, the slope of the curve is proportional to the k-spaceshift k₀. The slope δ_(x) may be obtained by, for example, simple linearregression, least squares, or the like.

In 812, a k-space shift value along the X axis may be determined basedon the spatial distribution of the phase difference in the image domain.A k-space shift value Δk_(x)′ along the X axis may be generated based onthe slope δ_(x). The k-space shift value may be obtained according tothe relationship between the image domain and the k-space. The k-spaceshift value may be determined by the shifting property of the Fouriertransform. In some embodiments, the k-space shift value Δk_(x)′ may bedetermined according to Equation (6):

$\begin{matrix}{{\Delta \; k_{x}^{\prime}} = {\frac{\delta_{x}}{2\pi} \cdot {m.}}} & (6)\end{matrix}$

where m may denote the number of the multiple readout points on theradial spoke along the X axis.

In 814, a candidate gradient delay value may be generated based on thek-space shift value. The candidate gradient delay value Δt may be thegradient delay value for gradient magnetic field in a certain directionin the coordinate system in the image domain. In some embodiments, thecandidate gradient delay value Δt may be determined by providing apredetermined coefficient. In some embodiments, the candidate gradientdelay value Δt may be determined by Equation (7):

Δt=C·Δk′ _(x).   (7)

where C may be defined as the predetermined coefficient. The coefficientC may be set by an operator, or by the MRI system 100. In someembodiments, the coefficient C may be determined based on the status ofthe system, time efficiency, convergence of the iteration, or the like.For example, a larger coefficient may be used to speed up theconvergence of the iteration. In some embodiments, the coefficient C maybe constant or variable. For example, the coefficient C may be aconstant during each iteration, such as 1, 0.5, 1.5, etc. In someembodiments, the coefficient C may be smaller than 2. As anotherexample, the coefficient may vary, having a value of 2 in the firstiteration, while a value of 1 in the second iteration.

In 816, a determination may be made as to whether a preset condition issatisfied. If the preset condition is satisfied, the process may proceedto 818. If the preset condition is not satisfied, the process may turninto another iteration within which operations 806 through 814 may berepeated to generate a new set of k-space data lines, and anothercandidate gradient delay value Δt may be generated accordingly based onthe new set of k-space data lines.

In some embodiments, the preset condition may include a maximum numberof iterations (for example, 10 times) that when the maximum number ofiterations is performed, the iteration may be stopped. The maximumnumber may be set by an operator, according to a default setting of theMRI system 100, etc. In some embodiments, the preset condition may be athreshold for the k-space shift value that when an eligible k-spaceshift value is obtained, the iteration may be stopped. The threshold fork-space shift value may be set by an operator, according to a defaultsetting of the MRI system 100, etc. For example, the iteration may beended when the k-space shift value obtained in the last iteration issmaller than a threshold. In some embodiments, the preset condition maybe that the difference between a plurality of (e.g., two or more)k-space shift values or a plurality of (e.g., two or more) gradientdelay values obtained in a plurality of (e.g., two or more) successiveiterations is smaller than a threshold. When the preset condition issatisfied, the process may proceed to 818.

In 818, the MRI system 100 may generate a gradient delay value based onthe candidate gradient delay value. The candidate gradient value Δtdetermined in 814 from the latest iteration may be provided as thegradient delay value ΔT. The gradient delay value ΔT may correspond tothe gradient delay in a certain direction in the I coordinate system.

In some embodiments, a local search algorithm may be performed after thegradient delay value ΔT is determined in the preceding operations. Thelocal search algorithm may sample a plurality of gradient delay valuesΔT_(i) (i=1, 2, 3, 4, . . . , n) based on the gradient delay value ΔT .In some embodiments, the sampled ΔT_(i) may be located within apredetermined range relative to ΔT, for example, ΔT±2 μsec. In someembodiments, the ΔT_(i) may be sampled at an interval within thesampling range, for example, at an interval of 0.1 μsec. The sampledΔT_(i) (i=1, 2, 3, 4, . . . , n) may be used to determine the value of aparameter. In some embodiments, the parameter may be a magnitudedifference between two image signals that correspond to two radialspokes in reverse directions in the k-space. In some embodiments, one ormore gradient delay values among ΔT_(i) (i=1, 2, 3, 4, . . . , n) may beselected according to the determined parameter. In some embodiments, theselected one or more gradient delay values ΔT_(i) may correspond to amaximum value, a minimum value, a median value, or other characteristicsof the parameter. In some embodiments, the selected gradient delayvalues ΔT_(i) may correspond to a minimum value of a magnitudedifference in the image domain between first k-space data line along afirst radial spoke and second k-space data line along a second radialspoke which is along the opposite direction relative to the first radialspoke. The selected one or more gradient delay values ΔT_(i) may replacethe gradient delay value ΔT.

It should be noted that the above description is provided for thepurposes of illustration, not intended to limit the scope of the presentdisclosure. For persons having ordinary skills in the art, multiplevariations and modifications may be achieved in the light of the presentdisclosure. However, those variations and modifications do not departfrom the scope of the present disclosure.

For example, the gradient delay value may be determined by k-space dataline along radial spokes in any direction of the k-space during thepre-scan. As another example, the gradient delay value determined in theprocess may be magnetic field gradient delay for X, Y or Z axis, or anyother directions in the coordinate system. As another example, thedetermination on whether the preset condition is satisfied may beperformed after 810, within which the spatial distribution of the phasedifference may be determined. Accordingly, the preset condition mayinclude the slope of the phase difference curve being below a threshold.a maximum number of iterations to be performed (for example, 20 times),or the like.

FIG. 9 is a flowchart of a process for generating an image based on thegradient delay value according to some embodiments of the presentdisclosure. In 902, k-space shift values for a radial spoke in thek-space may be determined based on the pre-scan. In some embodiments,the k-space shift values for data points along a radial spoke may bedifferent. In some embodiments, the k-space shift values for radialspokes in different directions in the k-space may be different. In someembodiments, k-space shift values for all radial spokes across thek-space may be determined before an MR image is generated.

In some embodiments, the k-space shift values for all radial spokes inthe k-space may be determined by repeating 802 through 812 as describedin FIG. 8. In some embodiments, the k-space shift values for all radialspokes in the k-space may be determined based on the gradient delayvalues in certain directions in the coordinate system. The determinationof the gradient delay values in certain directions in the coordinatesystem may be described elsewhere in the present application, forexample, FIG. 8 and the description thereof. In some embodiments, atleast three directions in the coordinate system may be selected and thegradient delay values for the three directions ΔT1, ΔT2, ΔT3 may bedetermined according to 802 through 818, respectively. It should benoted that the three directions may include a direction being orientedout of the plane constituted by the other two directions. In someembodiments, ΔT1, ΔT2, ΔT3 may be gradient delay values for the X axis,the Y axis, and the Z axis of the coordinate system. In someembodiments, an orthographic projection operation may be carried out todetermine the gradient delay values for the X axis, the Y axis, and theZ axis when ΔT1, ΔT2, ΔT3 are not the gradient delay values for the Xaxis, the Y axis, and the Z axis. The gradient delay values for the Xaxis, the Y axis, and the Z axis may be different from each other. Insome embodiments, the difference may relate to the condition of the MRIsystem 100 including, for example, the gradient coils, signal channels,or the like.

Referring back to the k-space, k-space shift values for all radialspokes may be determined based on the gradient delay values for the Xaxis, the Y axis, and the Z axis of the coordinate system. In someembodiments, a rotation matrix may be used for the transformationbetween the gradient delay values for the X axis, the Y axis, and the Zaxis and the k-space shift values.

In 904, a k-space data line may be acquired in an imaging scan. Theimaging scan may be an MRI scan for generating an image. In someembodiments, the imaging scan may be a 3D radial UTE scan. The imagingscan may be implemented by an RF pulse in conjunction with a gradientreversal (e.g., the dephasing gradient 602 and the rephrasing gradient603). In some embodiments, a plurality of gradient reversal includingmultiple dephasing gradients and rephrasing gradients may be applied togenerate multiple echo signals to fill the k-space. The dephasinggradient and the rephrasing gradient may be produced by a set of coilsmounted within the MR scanner 110.

In some embodiments, radial sampling may be performed in the imagingscan. For a three-dimensional radial sampling, the acquired k-space datain the imaging scan may be filled into the k-space along a radial spokestarting from the k-space center, and ending on a spherical surface inthe k-space. The sampling may continue to another radial spoke after thefilling of the current radial spoke is finished, until adequate k-spacedata lines are sampled to generate an image.

In 906, the acquired k-space data line may be calibrated based on thek-space shift values determined in 902. In some embodiments, k-spaceshift values for all radial spokes may be determined before, during, orafter the imaging scan. In some embodiments, the k-space shift value maycorrespond to the shift of the k-space data line on a radial spoke ofthe imaging scan. For example, the k-space shift value Δk_(r)′ may beused to calibrate the starting point shift of a radial spoke from (0, 0,0) to (k_(x), k_(y), k_(z)) in the k-space coordinate. Accordingly, thepositions of each k-space data point on the radial spoke may becorrected based on the k-space shift values.

In 908, an image may be generated based on the calibrated k-space dataline. An image may be reconstructed based on the calibrated k-space dataline generated by the imaging scan. The reconstruction methods togenerate the image may include Fourier transform (FT), fast Fouriertransform (FFT), non-uniform fast Fourier transform (NUFFT), etc. Insome embodiments, non-uniform k-space data points may be converted intoimage signal by way of an intermediate processing. In some embodiments,non-uniform k-space data points may be subject to an intermediateprocessing to generate corresponding uniform k-space data points. Merelyby way of example, the intermediate processing may include regridding,interpolation, etc. For example, non-uniform k-space data points may beconverted into uniform k-space data points by piecewise constantinterpolation, linear interpolation, polynomial interpolation, splineinterpolation, multivariate interpolation, etc. As another example,non-uniform k-space data points may be converted into uniform k-spacedata points by Jacobian regridding, Voronoi regridding, Jacksonregridding, Pipe regridding, etc. Then, the uniform k-space data pointsmay be transformed into an image signal. In some embodiments, thetransformation may be accomplished by FT, FFT, DFT, etc. In someembodiments, the non-uniform k-space data points may be transformed intoan image signal directly by non-uniform Fourier transform (NUFFT). Insome embodiments, apodization may be performed to correct for the effectof regridding kernel. In some embodiments, image signals forreconstructing different images may be collected to generate a combinedimage. In some embodiments, the image signals for each image mayoriginate from one of a plurality of gradient coils for receivingsignals from different areas of an imaged object.

In some embodiments, one or more post processing techniques may beapplied to the reconstructed image. The post processing techniques mayrelate to geometrical processing, arithmetic processing, imageenhancement, image restoration, 3D image reconstruction, or the like, ora combination thereof. Merely by ways of example, the post processingtechniques may include image magnification, distortion correction, imagesharpening, image softening, pseudo color processing, wiener filtering,etc. In some embodiments, the image may be compressed to a standardformat for handling, printing, storing, or transmitting MRI data, forexample, digital imaging and communications in medicine (DICOM). In someembodiments, the reconstructed image may be further processed and areport regarding the reconstructed image may be generated. In someembodiments, the reconstructed image and/or the generated report may beoutput to a related device (e.g., to be printed, to be displayed, or thelike). In some embodiments, the image may be generated by the imagingscan by repeating 902 through 906 until the gradient delay values ondesired spokes in the k-space are obtained and an image is generatedbased on the k-space data lines corrected based on the gradient delayvalues.

It should be noted that the above description is provided for thepurposes of illustration, not intended to limit the scope of the presentdisclosure. For persons having ordinary skills in the art, multiplevariations and modifications may be reduced to practice in the light ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure. For example, theorder of the steps in the process may be modified that 904 is processedprior to 902, i.e., the sampling of k-space data lines along a radialspoke in the imaging scan may be carried out before the k-space shiftvalue for the radial spoke is determined.

FIG. 10A through FIG. 10C illustrate three MR images reconstructed, byemploying a uniform gradient waveform, without gradient delay correctionaccording to some embodiments of the present disclosure. The arrows inthe images in FIG. 10A through 10C point to artifacts in the images of aphantom that may relate to the gradient delay. FIG. 10D through FIG. 10Fillustrate three MR images reconstructed, by employing a uniformgradient waveform, with gradient delay being corrected according to someembodiments of the present disclosure. No noticeable artifacts wereobserved in the images. FIG. 10G through FIG. 10I illustrate three MRimages reconstructed, by employing a non-uniform gradient waveform,without gradient delay correction according to some embodiments of thepresent disclosure. The arrows in the images in FIG. 10G through 10Ipoint to artifacts in the images of a phantom, which may relate to thegradient delay. FIG. 10J through FIG. 10L illustrate three MR imagesreconstructed by employing a nonrectangular gradient waveform, with thegradient delay being corrected, according to some embodiments of thepresent disclosure. No noticeable artifacts were observed in the images.The correction of the non-uniform gradient waveform are describedelsewhere in the present disclosure. See, for example, FIG. 8 and thedescription thereof.

FIG. 11A through FIG. 11C illustrate three MR images reconstructed, byemploying a uniform gradient waveform, without gradient delay correctionaccording to some embodiments of the present disclosure. The arrows inthe images in FIGS. 11A through 11C point to artifacts that may relateto the gradient delay. FIG. 11D through FIG. 11F illustrate three MRimages reconstructed, by employing a uniform gradient waveform, with thegradient delay being corrected according to some embodiments of thepresent disclosure. No noticeable artifacts were observed in the images.FIG. 11G through FIG. 11I illustrate three MR images reconstructed, byemploying a non-uniform gradient waveform, without gradient delaycorrection, according to some embodiments of the present disclosure. Thearrows in the images in FIGS. 11G through 11I point to artifacts thatmay relate to the gradient delay. FIG. 11J through FIG. 11L illustratethree MR images reconstructed by employing a non-uniform gradientwaveform, with the gradient delay being corrected, according to someembodiments of the present disclosure. No noticeable artifacts wereobserved in the images. The correction of the non-uniform gradientwaveform are described elsewhere in the present disclosure. See, forexample, FIG. 8 and the description thereof.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. The image producing procedures in the presentdisclosure may be effective in reducing, removing or eliminating othertypes of motion artifacts including, for example, the vascularpulsation, heart movement, and random motion of the subject beingscanned, or the like, or any combination thereof. The image producingprocedures in the present disclosure may be applied to whole body MRimaging, and the images produced may have more clear structural details.

Having thus described the basic concepts, it may be rather apparent tothose skilled in the art after reading this detailed disclosure that theforegoing detailed disclosure is intended to be presented by way ofexample only and is not limiting. Various alterations, improvements, andmodifications may occur and are intended to those skilled in the art,though not expressly stated herein. These alterations, improvements, andmodifications are intended to be suggested by this disclosure, and arewithin the spirit and scope of the exemplary embodiments of thisdisclosure.

Moreover, certain terminology has been used to describe embodiments ofthe present disclosure. For example, the terms “one embodiment,” “anembodiment,” and/or “some embodiments” mean that a particular feature,structure or characteristic described in connection with the embodimentis included in at least one embodiment of the present disclosure.Therefore, it is emphasized and should be appreciated that two or morereferences to “an embodiment” or “one embodiment” or “an alternativeembodiment” in various portions of this specification are notnecessarily all referring to the same embodiment. Furthermore, theparticular features, structures or characteristics may be combined assuitable in one or more embodiments of the present disclosure.

Further, it will be appreciated by one skilled in the art, aspects ofthe present disclosure may be illustrated and described herein in any ofa number of patentable classes or context including any new and usefulprocess, machine, manufacture, or composition of matter, or any new anduseful improvement thereof. Furthermore, aspects of the presentdisclosure may take the form of a computer program product embodied inone or more computer readable media having computer readable programcode embodied thereon.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including electro-magnetic, optical, or thelike, or any suitable combination thereof. A computer readable signalmedium may be any computer readable medium that is not a computerreadable storage medium and that may communicate, propagate, ortransport a program for use by or in connection with an instructionexecution system, apparatus, or device. Program code embodied on acomputer readable signal medium may be transmitted using any appropriatemedium, including wireless, wireline, optical fiber cable, RF, or thelike, or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of thepresent disclosure may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB. NET,Python or the like, conventional procedural programming languages, suchas the “C” programming language, Visual Basic, Fortran 2003, Perl, COBOL2002, PHP, ABAP, dynamic programming languages such as Python, Ruby andGroovy, or other programming languages. The program code may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider) or in a cloud computing environment or offered as aservice such as a Software as a Service (SaaS).

Furthermore, the recited order of processing elements or sequences, orthe use of numbers, letters, or other designations therefore, is notintended to limit the claimed processes and methods to any order exceptas may be specified in the claims. Although the above disclosurediscusses through various examples what is currently considered to be avariety of useful embodiments of the disclosure, it is to be understoodthat such detail is solely for that purpose, and that the appendedclaims are not limited to the disclosed embodiments, but, on thecontrary, are intended to cover modifications and equivalentarrangements that are within the spirit and scope of the disclosedembodiments. For example, although the implementation of variouscomponents described above may be embodied in a hardware device, it mayalso be implemented as a software only solution—e.g., an installation onan existing server or mobile device.

Similarly, it should be appreciated that in the foregoing description ofembodiments of the present disclosure, various features are sometimesgrouped together in a single embodiment, figure, or description thereoffor the purpose of streamlining the disclosure aiding in theunderstanding of one or more of the various inventive embodiments. Thismethod of disclosure, however, is not to be interpreted as reflecting anintention that the claimed subject matter requires more features thanare expressly recited in each claim. Rather, inventive embodiments liein less than all features of a single foregoing disclosed embodiment.

In some embodiments, the numbers expressing quantities of ingredients,properties such as molecular weight, reaction conditions, and so forth,used to describe and claim certain embodiments of the application are tobe understood as being modified in some instances by the term “about,”“approximate,” or “substantially.” For example, “about,” “approximate,”or “substantially” may indicate ±20% variation of the value itdescribes, unless otherwise stated. Accordingly, in some embodiments,the numerical parameters set forth in the written description andattached claims are approximations that may vary depending upon thedesired properties sought to be obtained by a particular embodiment. Insome embodiments, the numerical parameters should be construed in lightof the number of reported significant digits and by applying ordinaryrounding techniques. Notwithstanding that the numerical ranges andparameters setting forth the broad scope of some embodiments of theapplication are approximations, the numerical values set forth in thespecific examples are reported as precisely as practicable.

Each of the patents, patent applications, publications of patentapplications, and other material, such as articles, books,specifications, publications, documents, things, and/or the like,referenced herein is hereby incorporated herein by this reference in itsentirety for all purposes, excepting any prosecution file historyassociated with same, any of same that is inconsistent with or inconflict with the present document, or any of same that may have alimiting affect as to the broadest scope of the claims now or laterassociated with the present document. By way of example, should there beany inconsistency or conflict between the description, definition,and/or the use of a term associated with any of the incorporatedmaterial and that associated with the present document, the description,definition, and/or the use of the term in the present document shallprevail.

In closing, it is to be understood that the embodiments of theapplication disclosed herein are illustrative of the principles of theembodiments of the application. Other modifications that may be employedmay be within the scope of the application. Thus, by way of example, butnot of limitation, alternative configurations of the embodiments of theapplication may be utilized in accordance with the teachings herein.Accordingly, embodiments of the present application are not limited tothat precisely as shown and described.

1. A method for magnetic resonance imaging, comprising: acquiring afirst set of MR signals and a second set of MR signals by applying apulse sequence on a subject, the pulse sequence comprising at least animaging pulse and a pre-scan pulse; obtaining a first data line byfilling the first set of MR signals into k-space along a firsttrajectory; obtaining a second data line by filling the second set of MRsignals into k-space along a second trajectory; determining a candidatek-space shift based on the first data line and the second data line;performing a plurality of iterations, each of the iteration comprising:determining a candidate gradient delay based on the candidate k-spaceshift obtained from a prior iteration; updating the first data line andthe second data line based on the candidate gradient delay; and updatingthe candidate k-space shift based on the updated first data line and theupdated second data line; determining the candidate gradient delayobtained in the last iteration as the gradient delay; and reconstructingan image of the subject based on the gradient delay.
 2. The method ofclaim 1, further comprising obtaining a calibrated data line bycalibrating the first data line or the second data line based on thegradient delay, wherein the reconstructing an image of the subject isbased on the calibrated data line.
 3. The method of claim 1, wherein thefirst trajectory and the second trajectory pass through the k-spacecenter, and the first trajectory is opposite to the second trajectory.4. The method of claim 1, wherein the imaging pulse includes a UTEgradient, and the pre-scan pulse includes a dephaser gradient.
 5. Themethod of claim 1, further comprising performing a regridding operationon the first data line or the second data line.
 6. The method of claim1, wherein the determining the candidate k-space shift comprises:determining a phase difference in image domain based on the first dataline and the second data line; determining a slope value according tothe phase difference; and determining the candidate k-space shift basedon the slope value.
 7. The method of claim 6, wherein the iteration isterminated when the slope value obtained in the last iteration is belowa threshold.
 8. The method of claim 1, wherein the gradient delay is ina first direction corresponding to the first trajectory and the secondtrajectory.
 9. The method of claim 8, wherein the first direction is Xdirection, Y direction or Z direction.
 10. The method of claim 8,further comprising determining a second gradient delay in a seconddirection; determining a third gradient delay in a third direction, thethird direction is out of the plane defined by the first direction andthe second direction; acquiring a third set of MR signals by applying apulse sequence on a subject; obtaining a third data line by filling thethird set of MR signals into k-space along a third trajectory;determining a k-space shift along the third trajectory based on thefirst gradient delay, the second gradient delay and the third gradientdelay; and calibrating the third data line based on the third k-spaceshift along the third trajectory.
 11. The method of claim 10, whereinthe first direction is different from the second direction or the thirddirection.
 12. A magnetic resonance system, comprising: an MRI scannerconfigured to acquire a first set of MR signals and a second set of MRsignals by applying a pulse sequence on a subject, the pulse sequencecomprising at least an imaging pulse and a pre-scan pulse; and aprocessing module configured to: obtain a first data line by filling thefirst set of MR signals into k-space along a first trajectory; obtain asecond data line by filling the second set of MR signals into k-spacealong a second trajectory; determine a candidate k-space shift based onthe first data line and the second data line; perform a plurality ofiterations, each of the iteration comprising: determine a candidategradient delay based on the candidate k-space shift obtained from aprior iteration; update the first data line and the second data linebased on the candidate gradient delay; and update the candidate k-spaceshift based on the updated first data line and the updated second dataline; determine the candidate gradient delay obtained in the lastiteration as the gradient delay; and reconstruct an image of the subjectbased on the gradient delay.
 13. The system of claim 12, furthercomprising the processing module is configured to obtain a calibrateddata line by calibrating the first data line or the second data linebased on the gradient delay, wherein the reconstructing an image of thesubject is based on the calibrated data line.
 14. The system of claim12, wherein the first trajectory and the second trajectory pass throughthe k-space center, and the first trajectory is opposite to the secondtrajectory.
 15. The system of claim 12, wherein the imaging pulseincludes a UTE gradient, and the pre-scan pulse includes a dephasergradient.
 16. The system of claim 12, further comprising the processingmodule configured to perform a regridding operation on the first dataline or the second data line.
 17. The system of claim 12, wherein theprocessing module is configured to determine the candidate k-space shiftby: determining a phase difference in image domain based on the firstdata line and the second data line; determining a slope value accordingto the phase difference; and determining the candidate k-space shiftbased on the slope value.
 18. The system of claim 12, wherein the numberof iterations is less than
 20. 19. (canceled)
 20. A method fordetermining a gradient delay in a magnetic resonance system, comprising:acquiring a first set of MR signals and a second set of MR signals byapplying a pulse sequence on a subject, the pulse sequence comprising atleast an imaging pulse and a pre-scan pulse; obtaining a first data lineby filling the first set of MR signals into k-space along a firsttrajectory; obtaining a second data line by filling the second set of MRsignals into k-space along a second trajectory; iteratively determiningthe gradient delay based on a k-space shift in response to the firstdata line and the second data line determined based on the iterativeprocess including iteratively updating the first data line and thesecond data line after each iteration of the iterative process based onan updated gradient delay determined by the most recent iteration of theiterative process.